Home /Research /Swarm Intelligent Optimization Algorithms and Its Application in Mobile Robot Path Planning
SWARM

Swarm Intelligent Optimization Algorithms and Its Application in Mobile Robot Path Planning

Xiujuan Lei, Fei Wang, Ying Tan

Year
2016
Citations
3

Abstract

Mobile robot path planning is generally a kind of optimal problems, which is to find a best path of a track between a starting point to a goal point in the constraint conditions. Mobile robot path planning can be divided into two categories according to different environment planning awareness information: one is the global path planning and the other is the local path planning. We employed ACO, PSO, FA, FOA, FWA and ABC swarm intelligent optimization algorithms to optimize the global and local path planning of mobile robot, and gave the detailed implement steps and the comparing results to show the feasibility of using swarm intelligence optimization algorithms to solve the robot path planning problems. Request access from your librarian to read this chapter's full text.

Keywords

Motion planningMobile robotPath (computing)Computer scienceRobotMathematical optimizationAny-angle path planningSwarm intelligencePoint (geometry)Constraint (computer-aided design)

Related papers

Browse all SWARM papers